US9542226B2 - Operating programs on a computer cluster - Google Patents

Operating programs on a computer cluster Download PDF

Info

Publication number
US9542226B2
US9542226B2 US14/315,518 US201414315518A US9542226B2 US 9542226 B2 US9542226 B2 US 9542226B2 US 201414315518 A US201414315518 A US 201414315518A US 9542226 B2 US9542226 B2 US 9542226B2
Authority
US
United States
Prior art keywords
programs
execution
resource
program
cluster
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related, expires
Application number
US14/315,518
Other versions
US20150100968A1 (en
Inventor
Andreas Bieswanger
Ilija Leoshkevich
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
International Business Machines Corp
Original Assignee
International Business Machines Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by International Business Machines Corp filed Critical International Business Machines Corp
Assigned to INTERNATIONAL BUSINESS MACHINES CORPORATION reassignment INTERNATIONAL BUSINESS MACHINES CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BIESWANGER, ANDREAS, LEOSHKEVICH, ILIJA
Priority to US14/482,069 priority Critical patent/US10025630B2/en
Publication of US20150100968A1 publication Critical patent/US20150100968A1/en
Priority to US15/398,867 priority patent/US10310900B2/en
Application granted granted Critical
Publication of US9542226B2 publication Critical patent/US9542226B2/en
Expired - Fee Related legal-status Critical Current
Adjusted expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • G06F9/45533—Hypervisors; Virtual machine monitors
    • G06F9/45558—Hypervisor-specific management and integration aspects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5072—Grid computing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G06F9/5077—Logical partitioning of resources; Management or configuration of virtualized resources
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • G06F9/45533—Hypervisors; Virtual machine monitors
    • G06F9/45558—Hypervisor-specific management and integration aspects
    • G06F2009/45595—Network integration; Enabling network access in virtual machine instances

Definitions

  • the dedicated execution environment comprises a virtual machine operated by an operating system
  • the generating of the one or more dedicated execution environments using the identified cluster resources comprises: creating the virtual machine using one or more identified virtual resources; connecting the identified non-virtual real hardware resource with the variable configuration to the virtual machine; and installing the operating system on the virtual machine.
  • FIG. 12 is a block diagram of software for operating programs on a computer cluster.
  • aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.
  • the computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
  • the first and the second hypervisor and the first and the second virtual machines are the virtual resources, while all other resources depicted in FIG. 1 are the non-virtual real hardware resources with the variable configurations.
  • the company network links the hardware resource, the hypervisor manager, the hardware resource manager, and the computer system for operating programs.
  • the first hypervisor network links the hypervisor manager, the first hypervisor, and the second hypervisor.
  • the second hypervisor network links the first virtual machine and the first hypervisor.
  • the third hypervisor network links the second virtual machine and the second hypervisor.
  • Each cluster resource has a configuration and a type. Each type has a unique identification and descriptions of operations which can be performed by the cluster resource of each type.
  • the one or more dedicated execution environments for execution of the programs using the identified cluster resources are generated.
  • the cluster resource is identified upon a request for usage of the program.
  • the identified cluster resource has the specified type.
  • the configuration description of the identified cluster resource comprises the specified configuration description. The latter identification criterion can be readily understood on a basis of the aforementioned example regarding a volume of memory.
  • a request of the program for modification of the variable configuration of the non-virtual real hardware resource with the variable configuration is received.
  • the process block 140 is executed.
  • At least a portion of the programs may have execution conflicts.
  • Each program has a unique identification.
  • the unique identifications of the programs having execution conflicts are stored in the list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently. For instance the execution conflict may be caused by the pair of programs requesting concurrently the cluster resource for the exclusive usage.
  • the selection of the program that has to be aborted can be performed by using one or a combination of the following criteria: the aborted program of the pair of programs having the execution conflict detected is the program that has a shorter duration of execution in comparison with another program of the pair, the aborted program of the pair of programs having execution conflict detected is the program which has a lower percentage of executed workload in comparison with the other program of the pair, the aborted program of the pair of the programs having executed conflict detected is the program which has a bigger number of the cluster resources requested for usage in comparison with the other program of the pair.
  • FIG. 5 depicts a flowchart of process blocks for splitting of the programs in the groups comprising the programs having no execution conflicts with each other and an example of execution of the flowchart of the process blocks.
  • This flowchart is an example implementation of the process block 210 .
  • all possible variants of splitting of the programs in the groups are generated.
  • all groups comprising programs having the execution conflicts with each other are deleted.
  • the variant of splitting comprising the list number of the groups is selected.
  • the operation of this flowchart can be readily understood on the basis of the following example. For instance there are three programs, A, B and C and there is a need for generation of an optimum schedule for execution of these programs. There are two pairs of programs having execution conflicts: A B and B C.

Abstract

A mechanism is provided for operating programs on a computer cluster comprising cluster resources. The cluster resources comprise non-virtual real hardware resources with variable configurations and virtual resources. Each cluster resource has a configuration description and a type. Each type has a unique type identification and descriptions of operations that can be performed by the cluster resource of the each type. Each program is operable for: requesting usage of the cluster resource specifying the type and the configuration description; and requesting a modification of the variable configuration of the non-virtual real hardware resource with the variable configuration. Execution of each program requires the dedicated execution environment on the computer cluster. The generation of each dedicated execution environment requires one or more dedicated virtual resources and one or more dedicated non-virtual real hardware resources with the variable configurations.

Description

BACKGROUND
The invention refers to a mechanism for operating programs on a computer cluster comprising cluster resources.
Effective operating of computer programs in complex environments comprising virtual and non-virtual real hardware resources is an everlasting task of the computer science. Various virtualization software products are developed in order to create virtual machines for execution of the computer programs. The virtual machines provide optimum functionalities for execution of the computer programs. The problem of operation of the computer programs gets more complicated when execution of programs requires heterogeneous environments comprising virtual and non-virtual real hardware resources. IBM zManager is one of the solutions addressing the problem mentioned above. zManager is operable for controlling a System z mainframe with System x and System p blade center extensions. Functionality provided by zManager ranges from configuration of individual System z/x/p units to creating heterogeneous virtual machines being connected into virtual networks and having storage area network (SAN) attached.
SUMMARY
The present invention provides embodiments that fill the need of improved operating of computer programs on computer clusters comprising virtual and non-virtual real hardware resources. It should be appreciated that the present invention can be implemented in numerous ways, including as a process, a method, an apparatus, a system, a device, or a computer program product carrying computer executable code for execution by a processor controlling the apparatus. Several inventive embodiments are described below.
One embodiment provides for a computer implemented method for operating programs executable on a computer cluster. The computer cluster comprises the following cluster resources: non-virtual real hardware resources with variable configurations and virtual resources. Each cluster resource has a configuration description and a type. Each type has a unique type identification and descriptions of operations which can be performed by the cluster resource of the each type. Each program is operable for: requesting usage of the cluster resource specifying the type and the configuration description; and requesting a modification of the variable configuration of the non-virtual real hardware resource with the variable configuration. Execution of each program requires a dedicated execution environment on the computer cluster. Generation of each dedicated execution environment requires the following dedicated resources: one or more dedicated virtual resources and one or more dedicated non-virtual real hardware resources with the variable configurations. Each dedicated resource has an execution environment specific type and an execution environment specific configuration description. The method comprises the following steps.
The cluster resources for generation of the one or more dedicated execution environments are identified. Each identified cluster resource matches one dedicated resource. Each identified cluster resource and the matching dedicated resource have the same type and the configuration description of each identified cluster resource comprises the execution environment specific configuration description of the matching dedicated resource.
The one or more dedicated execution environments for execution of programs are generated using the identified cluster resources.
The cluster resource is identified upon a request of the program for usage of the cluster resource. The identified cluster resource has the specified type. The configuration description of the identified cluster resource comprises the specified configuration description.
In response to a request of the program for a modification of the variable configuration of the non-virtual real hardware resource with the variable configuration executing the following is performed: the non-virtual real hardware resource with the variable configuration is reserved for exclusive usage by the program, and after the reserving of the non-virtual real hardware resource with the variable configuration for exclusive usage by said program the requested modification of the variable configuration of said non-virtual real hardware resource with the variable configuration is executed.
A record of the executed modifications of the variable configuration of the non-virtual real hardware with the variable configuration is generated.
The executed modifications of the variable configuration of said non-virtual real hardware resource with the variable configuration are rolled back using the record after execution of said program is ended.
After the rolling back of the executed modifications, the reserving of the non-virtual real hardware resource with the variable configuration is cancelled.
In another embodiment, at least a portion of the programs has execution conflicts. Each program has a unique identification. The unique identifications of the programs having execution conflicts are stored in a list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently.
The computer implemented method further comprises the following: splitting the programs in a minimum possible number of groups, wherein each group comprises no pairs of the programs having corresponding pairs of the unique identifications in the list; generating a schedule for execution of the programs is generated, wherein all programs of each group are scheduled for concurrent execution and the groups of the programs are scheduled for consecutive execution, wherein consecutive execution of the groups is prioritized according to the number of the programs in the groups, wherein the group comprising the highest number of programs is scheduled as the first one for execution and the group comprising the least number of programs is scheduled as the last one for execution, wherein in a case when two groups comprise the same number of programs these groups are prioritized at random; starting execution of the programs according to the schedule in the one or more created execution environments; detecting an execution conflict of a pair of the programs; aborting one of the programs of the pair of the programs having the execution conflict detected; updating the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected; generating a new schedule for execution of the aborted program and programs for which execution was not started yet; starting execution of the programs according to the new schedule in the one or more created execution environments after execution of the group comprising another program of the pair is finished.
In yet another embodiment, at least a portion of programs has execution conflicts. Each program has a unique identification. The unique identifications of the programs having execution conflicts are stored in a list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently.
The computer implemented method further comprises the following: a) generating an additional group; b) assigning one of the not yet assigned programs having no execution conflicts with all programs assigned to the additionally generated group; c) repeating steps b)-c) until there are no programs left which have no execution conflicts with any of the programs of the additionally generated group; d) iteratively repeating the steps a)-d), wherein the repeating is continued until all programs are assigned to one or more groups, wherein exactly one additional group is generated during each repeating of the steps a)-d), wherein all pairs comprising at least one unique identification of any of the programs assigned to any previously generated additional group are considered as being deleted from the list during the subsequent repeating of the steps a)-d); generating a schedule for execution of the programs, wherein all programs of each group are scheduled for concurrent execution and the groups of the programs are scheduled for consecutive execution, wherein consecutive execution of the groups is prioritized according to the number of the programs in the groups, wherein the group comprising the highest number of programs is scheduled as the first one for execution and the group comprising the least number of programs is scheduled as the last one for execution, wherein in a case when two groups comprise the same number of programs these groups are prioritized at random; starting execution of the programs according to the schedule in the one or more created execution environments; detecting an execution conflict of a pair of the programs; aborting one of the programs of the pair of the programs having the execution conflict detected; updating the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected; after the updating of the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected identifying all programs, which pairs in the list comprise the unique identification of the aborted program; identifying whether one or more not yet executed groups do not comprise any identified program, if yes assigning the aborted program to the not yet executed group not comprising any identified programs and having the highest priority for execution among the not yet executed groups and if no scheduling execution of the aborted program after execution of the last group.
In yet another embodiment, the aborted program of the pair of the programs is the program having a bigger number of the cluster resources requested for usage in comparison with another program of said pair.
In yet another embodiment, the aborted program of the pair of the programs is the program having lower percentage of the executed workload in comparison with another program of the pair.
In yet another embodiment, the aborted program of the pair of the programs is the program having a shorter duration of execution in comparison with another program of the pair.
In yet another embodiment, the cluster resources are hierarchically allocated within one or more resource parent-child relationship trees and linked by resource parent-child relationships with each other within the one or more resource parent-child relationship trees. Each resource parent-child relationship tree matches a type parent-child relationship tree comprising the hierarchically allocated types linked by type parent-child relations within the type parent-child relationship tree, wherein each resource parent-child relationship tree has one top root cluster resource, wherein each type parent-child relationship tree has one top root type, wherein each top root cluster resource of each resource parent-child relationship tree has the top root type of the type parent-child relationship tree matching the each resource parent-child relationship tree, wherein the resource parent-child relationships match the type parent-child relationships of their types.
The computer implemented method further comprises the following: identifying first fragments of the one or more type parent-child relationship trees linking the one or more top root types of the first fragments with the environment specific types allocated at bottoms of the first fragments; identifying second fragments of the one or more resource parent child-relationship trees matching the first fragments, wherein the identifying of the cluster resources for the generation of the one or more dedicated environments is performed using the cluster resources allocated at the bottoms of the second fragments, wherein all cluster resources allocated at bottoms of the second fragments have the environment specific types; storing the second fragments in a registry; identifying one or more first adjacent fragments of the one or more resource parent-child relationship trees using a lazy thunk identification, wherein each first adjacent fragment is adjacent to one of the second fragments; updating the registry with the one or more identified first adjacent fragments.
In yet another embodiment, the computer implemented method further comprises the following: checking whether at least one of the cluster resources allocated in the fragments of the one or more resource parent-child relationship trees stored in the registry has the specified type and has the configuration description comprising the specified configuration description, if yes the identifying of the cluster resource upon the request of the program for usage of the cluster resource is performed using the fragments of one or more resource parent-child relationship trees stored in the registry and if no, performing the following: identifying one or more third fragments of the one or more type parent-child relationship trees linking the one or more top root types of one or more type parent-child relationship trees with the specified type allocated at one or more bottoms of the one or more third fragments; identifying one or more fourth fragments of one or more resource parent child-relationship trees matching the one or more third fragments, wherein the identifying of the cluster resource upon the request of the program for usage of the cluster resource is performed using the cluster resources allocated at one or more bottoms of the one or more fourth fragments, wherein all cluster resources allocated at the one or more bottoms of the one or more fourth fragments have the specified type; updating registry with all fourth fragments; identifying one or more second adjacent fragments of one or more resource parent-child relationship trees using the lazy thunk identification, wherein each second adjacent fragment is adjacent to one of the one or more fourth fragments; and updating the registry with the one or more second adjacent fragments.
In yet another embodiment, the identifying of the one or more fragments of the one or more resource parent child-relationship trees is performed applying one or more predefined identification constrains restricting the identifying of the fragments of the one or more resource parent-child relationship trees.
In yet another embodiment, the dedicated execution environment comprises a virtual machine operated by an operating system, wherein the generating of the one or more dedicated execution environments using the identified cluster resources comprises: creating the virtual machine using one or more identified virtual resources; connecting the identified non-virtual real hardware resource with the variable configuration to the virtual machine; and installing the operating system on the virtual machine.
Yet another embodiment provides for a computer system for operating programs executable on a computer cluster. The computer system is operable for performing all or a portion of the steps of the aforementioned computer implemented method.
Yet another embodiment provides for a computer program product, in particular a computer readable medium. The computer program product carries computer executable code for execution by a processor controlling an apparatus. Execution of the instructions cause the processor to perform all or a portion of steps of the aforementioned computer implemented method.
BRIEF DESCRIPTION OF THE DRAWINGS
The present invention will be readily understood by the following detailed description in conjunction with the accompanying drawings.
FIG. 1 is a block diagram of an example computer cluster.
FIG. 2a-b is a flowchart of process blocks for operating programs on a computer cluster.
FIG. 3 is a flowchart of process blocks for operating programs on a computer cluster according to a schedule.
FIG. 4 is a flowchart of process blocks for splitting of programs in groups used for generation of an execution schedule and execution of the programs according to the execution schedule.
FIG. 5 is a flowchart of process blocks for splitting of programs in groups and an example of execution of the flowchart of the process blocks.
FIG. 6 is an example fragment of a type parent-child relationship tree of types of cluster resources.
FIG. 7 is an example fragment of a resource parent-child relationship tree of cluster resources.
FIG. 8 is a flowchart of process blocks for identification of cluster resources.
FIG. 9 is another example fragment of the resource parent-child relationship tree of cluster resources.
FIG. 10 is another flowchart of process blocks for identification of cluster resources.
FIG. 11 is a flowchart of process blocks for generating a dedicated environment.
FIG. 12 is a block diagram of software for operating programs on a computer cluster.
FIG. 13 is a fragment of a program code.
FIG. 14 is an example of a hierarchy and parent-child relationships of types of computer cluster resources.
 DETAILED DESCRIPTION
Effective operating/managing of execution of programs on a computer cluster requires a lot of issues to be addressed in an effective and coherent way. The simplest solution comprising creation of a virtual machine for each program and reduction of cluster resource sharing to a minimum in order to avoid sharing conflicts is a good option only in a case when resources of the computer cluster are not limited. As usual, it is not the case. Thus, in order to maximize effectiveness of the computer cluster utilization there is a need for a solution enabling the following: effective identification and management of cluster resources needed for execution of the programs and generation of an effective schedule for execution of programs, wherein execution conflicts of the programs are minimized. Special measures have to be taken for management of cluster resources with variable configurations. The program may execute changes in configurations of the cluster resources. These changes may compromise execution of other programs sharing the cluster resource having variable configuration modified by one of the programs. Moreover, these changes may cause further a malfunction of the cluster resource. This problem gets more complicated when the program has modified the variable configuration of a non-virtual real hardware resource. In a case when the program that has executed these changes is aborted, there is no other way to restore this resource to its original state, other than rebooting it. This operation may cost a lot of time and compromise performance of the computer cluster. As it will be clearly seen from the following description the present invention addresses these issues in an effective way.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.
Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing: In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wire line, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming
language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
It will also be noted that each process block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
FIG. 1 illustrates an example block diagram of a computer cluster 10 used for execution of programs. The computer cluster comprises the following cluster resources: non-virtual real hardware resources with variable configurations and virtual resources. Merely by means of example, the computer cluster further comprises the following cluster resources: a hardware resource 20, a company network 40, a computer system for operating programs 50, a hardware resource manager 60, a hypervisor manager 30, a first virtual machine 96, a second hypervisor network 70, a first hypervisor 80, a first hypervisor network 90, a second hypervisor 92, a third hypervisor network 94, a disk array 51, and a second virtual machine 99. In the aforementioned example, the first and the second hypervisor and the first and the second virtual machines are the virtual resources, while all other resources depicted in FIG. 1 are the non-virtual real hardware resources with the variable configurations. The company network links the hardware resource, the hypervisor manager, the hardware resource manager, and the computer system for operating programs. The first hypervisor network links the hypervisor manager, the first hypervisor, and the second hypervisor. The second hypervisor network links the first virtual machine and the first hypervisor. The third hypervisor network links the second virtual machine and the second hypervisor. Each cluster resource has a configuration and a type. Each type has a unique identification and descriptions of operations which can be performed by the cluster resource of each type. The types can be implemented among other ways as follows: as dynamically linked libraries, as operating system drivers, and as network services. The configuration of the cluster resource is a set of characteristics describing the cluster resource and its current state. For instance, the server may have the following configuration: a server chassis serial number, an operating mode of the chassis management module having two possible values ‘primary’ and ‘standby’, a central processing unit temperature, and a total and currently available amount of hypervisor memory. Execution of each program requires a dedicated execution environment on the computer cluster. Generation of each dedicated execution environment requires the following dedicated resources: one or more dedicated virtual resources and one or more dedicated non-virtual real hardware resources with the variable configurations. For instance, the dedicated execution environment may comprise two servers and a network switch. Each dedicated resource has an execution environment-specific type and an execution environment-specific configuration description. Each program is operable for: requesting usage from the cluster resource specifying the type and the configuration description, and requesting a modification of the variable configuration for the non-virtual real hardware resource with the variable configuration.
FIG. 2a-b illustrates process blocks of a computer implemented method of operating programs executable on the computer cluster. The method comprises the following process blocks. In the process block 100 the cluster resources required for generation of the one or more dedicated execution environments are identified. Each identified cluster resource matches one dedicated resource. Each identified cluster resource and the matching dedicated resource have the same type. The configuration description of each identified cluster resource comprises the execution environment specific configuration description of the matching dedicated resource. The latter identification criterion can be readily understood on a basis of the following example. For instance the execution environment specific configuration description of the dedicated resource comprises 40 Gb of a solid state drive memory. Any cluster resource having not less than 40 Gb of the solid state drive memory can be identified according to this example criterion. In the next process block 110, the one or more dedicated execution environments for execution of the programs using the identified cluster resources are generated. In the process block 120 the cluster resource is identified upon a request for usage of the program. The identified cluster resource has the specified type. The configuration description of the identified cluster resource comprises the specified configuration description. The latter identification criterion can be readily understood on a basis of the aforementioned example regarding a volume of memory. In the process block 130 a request of the program for modification of the variable configuration of the non-virtual real hardware resource with the variable configuration is received. In response to receiving of the request of the program for the modification of the variable configuration of the non-virtual real hardware resource with the variable configuration in the process block 130, the process block 140 is executed. In the process block 140 the non-virtual real hardware resource with the variable configuration which variable configuration was requested to be modified by the program, is reserved for exclusive usage by this program. Afterwards in the process block 150 the variable configuration of the reserved non-virtual real hardware resource with the variable configuration is modified as it was specified in the request of the program. In the process block 160 a record of the executed modifications of the variable configuration of the reserved non-virtual real hardware resource with the variable configuration is generated. In the process block 170 the executed modifications of the variable configuration of the reserved non-virtual real hardware resource with the variable configuration is rolled back using the record after execution of the program, which has requested the modifications, is ended. The rolling back can be readily understood on the basis of the following examples. For instance, the server operates a list of services within an operating system installed on the server. Changes in the list of services are considered as modification of the variable configuration of the server. The list of services is stored in the record prior to executing changes in the list of services. When there is a need for rolling back the changes in the list of services running on the server, the list of services running within the operating system on the server is restored back according to the list of services stored in the record. Another example is a modification of a line in the configuration of a Hypertext Transfer Protocol (HTTP) server running on a non-virtual real hardware server. Rolling back of the variable configuration in this case constitutes the location of this modified line in the configuration file of the HTTP server and restoring it to an original state. In the process block 180 after the rolling back of the executed modifications of the variable configuration of the reserved non-virtual real hardware resource with the variable configuration the reservation of this cluster resource is cancelled.
At least a portion of the programs may have execution conflicts. Each program has a unique identification. The unique identifications of the programs having execution conflicts are stored in the list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently. For instance the execution conflict may be caused by the pair of programs requesting concurrently the cluster resource for the exclusive usage.
FIG. 3 illustrates a flowchart of process blocks of operating programs having execution conflicts on the computer cluster. In the process block 200 the programs are split in a minimum possible number of groups, wherein each group comprises no pairs of the programs having corresponding pairs of the unique identifications in the list. In other words each group comprises no pairs of the programs having the execution conflicts with each other. In process block 210 a schedule for execution of the programs is generated. All programs of each group are scheduled for concurrent execution and the groups of the programs are scheduled for consecutive execution. Consecutive execution of the groups is prioritized by number of the programs in the groups. The group comprising the highest number of the programs is scheduled as the first one for execution and the group comprising the least amount of programs is scheduled as the last one for execution. In a case when the groups comprise the same number of programs, then these groups are prioritized at random. In the process block 220 execution of the programs according to the schedule is started in the one or more created execution environments. In the process block 230 the execution conflict of the pair of the programs is detected. In the process block 240 one of the programs of said pair of the programs having the execution conflict detected is aborted. In the process block 250 the list is updated with the pair of the unique identifications of said pair of the programs having the execution conflict detected. In the process block 260 a new schedule for execution of the aborted program and the programs for which execution was not started yet is generated. In the process block 270 the programs are executed according to the new schedule in the one or more created execution environments after execution of the group comprising another program of the pair comprising the aborted program is finished.
FIG. 4 illustrates a flowchart of process blocks for splitting of the programs in groups used for generation of an execution schedule, generation of the execution schedule, and execution of the programs according to the execution schedule. In a process block 201 an additional group is generated. In the process block 202 one of the not yet assigned programs having no execution conflicts with all programs assigned to the additionally generated group is assigned to the additionally generated group. After execution of the process block 202 the decision process block 203 is executed. In the decision process block 203 it is checked whether there are any programs left which have no execution conflicts with any of the programs of the additionally generated group. If there are one or more programs left which have no execution conflicts with any of the programs of the additionally generated group then the process block 202 is executed. If there are no programs left that have no execution conflicts with any of the programs of the additionally generated group then a decision process block 204 is executed. In the decision process block 204 it is checked whether all programs are assigned to one or more groups. If not all programs are assigned to one or more groups then the process blocks 201, 202 and 203 are executed again. If all programs are assigned to one or more groups then a process block 261 is executed. In the process block 261 the process blocks 210, 220, 230, 240, and 250 are executed as described above and depicted in FIG. 3. In the process block 280 after the updating of the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected all programs are identified which pairs in the list comprise the unique identification of the aborted program. In the process block 290 it is checked whether one or more not yet executed groups do not comprise any identified program. When one or more not yet executed groups do not comprise any identified program then the process block 291 is executed, otherwise the process block 292 is executed. In the process block 291 the aborted program is assigned to the not yet executed group not comprising any identified problem and having the highest priority for execution among the not yet executed groups. In the process block 291 execution of the aborted program is scheduled after execution of the last group.
In the process block 240 the selection of the program that has to be aborted can be performed by using one or a combination of the following criteria: the aborted program of the pair of programs having the execution conflict detected is the program that has a shorter duration of execution in comparison with another program of the pair, the aborted program of the pair of programs having execution conflict detected is the program which has a lower percentage of executed workload in comparison with the other program of the pair, the aborted program of the pair of the programs having executed conflict detected is the program which has a bigger number of the cluster resources requested for usage in comparison with the other program of the pair.
FIG. 5 depicts a flowchart of process blocks for splitting of the programs in the groups comprising the programs having no execution conflicts with each other and an example of execution of the flowchart of the process blocks. This flowchart is an example implementation of the process block 210. In the process block 212 all possible variants of splitting of the programs in the groups are generated. In the process block 214 all groups comprising programs having the execution conflicts with each other are deleted. In the process block 215 the variant of splitting comprising the list number of the groups is selected. The operation of this flowchart can be readily understood on the basis of the following example. For instance there are three programs, A, B and C and there is a need for generation of an optimum schedule for execution of these programs. There are two pairs of programs having execution conflicts: A B and B C. Execution of the process block 212 results in a generation of the following variants: a first variant [A, B, C], a second variant [AB, C], a third variant [AC, B], a fourth variant [BC, A], and a fifth variant [ABC]. In the first variant the programs are split in three groups, wherein each group comprises one program. In the second, third, and fourth variants the programs are split in two groups, wherein one group comprises two programs and another group comprises one program. In the fifth variant all programs are in one group. In the process block 214 the fifth, the fourth and second variant are deleted, since these variants comprise groups of the programs having the execution conflict within one of the groups. In the process block 215 the third variant is selected since it comprises fewer groups than the first variant.
The cluster resources may be hierarchically allocated within one or more resource parent-child relationship trees and linked by resource parent-child relationships with each other within the one or more resource parent-child relationship trees. Each resource parent-child relationship tree matches a type parent-child relationship tree 400 comprising the hierarchically allocated types linked by type parent-child relations within the type parent-child relationship tree. The resource parent-child relationships match the type parent-child relationships of their types. Each resource parent-child relationship tree has one top root cluster resource 501. Each type parent-child relationship tree has one top root type 401.
FIG. 6 depicts an example type parent-child relationship tree 400. The type ‘root resource’ 401 is a root element of the type parent-child relationship tree 400. The type ‘root resource’ has a type ‘ensemble’ 410 as its child. The type ‘ensemble’ has the type ‘root resource’ as its parent. The type ‘ensemble’ has the following child types: a ‘network’ 420, a ‘hardware pool manager’ 470, and a ‘hypervisor’ 450. The type ‘network’ has the following child types: a ‘company network’ 430 and a ‘hypervisor network’ 440. The type ‘hypervisor’ has the following child types: a ‘virtual machine’ 460 and a ‘virtual resource’ 490. The type ‘hardware pool manager’ has a type ‘hardware resource’ 480 as its child type.
FIG. 7 depicts a fragment of a resource parent-child relationship tree 500 matching the type parent-child relationship tree 400. The root resource 500 is the root element of the resource parent-child relationship tree. It has the type ‘root resource’ 401 depicted in FIG. 7. The root resource 501 has a first ensemble 510 and a second ensemble 511 as its child resources. The first ensemble and the second ensemble have the type ‘ensemble’ as depicted in FIG. 7. The resource parent-child relationships for the root resource with its child resources (the first ensemble and the second ensemble) correspond to the type parent-child relationship of their types depicted in FIG. 7. The first ensemble 510 has a first hardware pool manager 550 as its child resource. The second ensemble has a second hardware pool manager 570 as its child resource. The hardware pool managers have the type ‘hardware pool manager’ 470 as depicted in FIG. 7. The resource parent-child relationships between the ensembles and the hardware pool managers correspond to the type parent-child relationship of their types as depicted in FIG. 7. The first hardware pool manager 550 has a first hardware resource 560 and a second hardware resource 580 as its child resources. The second hardware pool manager 570 has a third hardware resource 590 and a fourth hardware resource 592 as its child resources. The hardware resources have the type ‘hardware resource’ 480 as depicted in FIG. 7. The resource parent-child relationships between the hardware pool managers and the hardware resources correspond to the type parent-child relationship of their types as depicted in FIG. 7.
FIG. 8 illustrates a flowchart of process blocks for identification of the cluster resources. The identification of the cluster resources is needed in the process block 100 and the process block 120 of the flowchart diagram depicted in FIG. 2. In the process block 300 first fragments of the one or more type parent-child relationship trees linking the one or more root elements or the one or more type parent-child relationship trees with the environment-specific types allocated in bottoms of the first fragments are identified. The environment specific types are specified in the process block 100. Identification of the first fragments may be executed using a bottom-up approach. First the parent types of environment specific types are identified. Afterwards the parent types of the identified types are identified. The latter procedure is performed until the root type of the first fragments is identified. In process block 310 second fragments of the one or more resource parent-child relationship trees matching the first fragments are identified. All cluster resources allocated at the bottoms of the second fragments have the environment specific types. The identifying of the cluster resources for the generation of the one or more dedicated execution environments as specified in the process block 100 is performed using the cluster resources allocated at the bottoms of the second fragments. Identification of the cluster resources in this process block may be performed using top-down approach. First the top root cluster resources having the top root types are identified. Afterwards the child cluster resources of the top root cluster resources are identified, wherein the identified child cluster resources have the same types as child types of the top root types within the first fragments. The latter procedure is repeated until the cluster resources having environment specific types are reached. In the process block 320 the second fragments are stored in a registry. The storing of the second fragments in the registry may accelerate further identification of another needed cluster resource. It may be a lot faster and easier to find the needed cluster resource in the registry rather than performing the process blocks 300 and 310 again, because the registry may comprise at least one following type of cluster resource information/characterization: physical addresses of the cluster resources, logical addresses of the cluster resources, configurations of the cluster resources. In a process block 340 one or more first adjacent fragments of the one or more resource parent-child relationship trees are identified using a lazy thunk identification. Each first adjacent fragment is adjacent to the one of the second fragments. The lazy thunk identification of the one or more first adjacent fragments may be a low priority computer process. It serves the purpose of further collection of cluster resources that are not yet stored in the registry and for which identification was not yet requested. As a result the registry will contain even more cluster resources and any subsequent identification of the needed cluster resource may be performed faster by searching first in the registry. In the process block 350 the registry is updated with the one or more identified first adjacent fragments.
Performance of the flowchart depicted on the FIG. 8 can be readily understood on a basis of the following example illustrated in the FIG. 7. Suppose the cluster resource having the type ‘hardware resource’ has to be identified. Processing of the type parent-child relationship tree 400 according to the process block 300 results in identification of the first fragment comprising the type ‘root resource’ 401, the type ‘ensemble’ 410, the type ‘hardware pool manager’ 470, and the type ‘hardware resource’ 480. The first fragment of the type parent-child relationship tree has the second matching fragment 500 of the resource parent-child relationship tree. The second fragment comprises the root resource 501, the first ensemble 510, the second ensemble 511, the first hardware pool manager 550, the second hardware pool manager 570, the first hardware resource 560, the second hardware resource 580, the third hardware resource 590, and the fourth hardware resource 592. As a result of execution of the process block 310 the needed hardware resource is identified using the first, the second, the third, and the fourth hardware resource in the process block 110. Execution of the process block 340 results in performing of a first lazy thunk identification 520 of the not yet identified child cluster resources of the first ensemble 510 and a second lazy thunk identification 530 of the not yet identified child cluster resources of the second ensemble 511.
The identification of the one or more fragments of the one or more resource parent-child relationship trees may be performed by applying one or more predefined identification constraints restricting the identifying of the fragments of the one or more resource parent-child relationship trees. Going back to the aforementioned example this procedure can be illustrated as follows. For instance it is known upfront that the first ensemble 510 will be shut down for maintenance during execution of the programs. Therefore, it may not be selected for the creation of the one or more dedicated environments. During top-down identification of the needed hardware resource for the generation of the one or more dedicated execution environments a custom child getter comprising the aforementioned constraint is activated. As a result of identification of the cluster resources using the custom child getter is depicted in FIG. 9. First the root resource 501 is identified as it was described previously. Afterwards only the second ensemble 511 is identified as the child cluster resource of the root resource 501 because of applying the custom child getter restricting the identification of the first ensemble 510. Afterwards only the third hardware resource 590 or the fourth hardware resource 592 is identified in the same way as it is described above. However, the not yet identified child cluster resources of the root resource 501 may be identified by performing the third lazy thunk identification 594. Other not yet identified child cluster resources of the second ensemble 511 may be identified by performing the second lazy thunk identification 530.
The registry may be further used for the identifying of the cluster resource upon the request of the program for usage of the cluster resource as described in the process block 120.
FIG. 10 illustrates a flowchart for identifying of the cluster resource upon the request of the program. In a decision process block 360 it is checked whether the registry comprises the cluster resource requested for usage by the program. If this statement is correct the process block 370 is performed, wherein the identifying of the cluster resource upon the request of the program for usage of the cluster resource is performed using the fragments of the one or more resource parent-child relationship trees stored in the registry. If this statement is not correct the following process blocks are defined. In the process block 380 one or more third fragments of the one or more type parent-child relationship trees linking one or more top root types with a specified type allocated at one or more bottoms of the one or more third fragments are identified. In a process block 390 one or more fourth fragments of the one or more resource parent-child relationship trees matching the one or more third fragments are identified. In this case the identifying of the cluster resources upon the request of the program for usage of the cluster resource is performed using the cluster resources allocated at the one or more bottoms of the one or more fourth fragments. All cluster resources allocated to the one or more bottoms of the one or more fourth fragments have the specified type. In the process block 392 the registry is updated with all fourth fragments. In the process block 394 one or more second adjacent fragments of the one or more resource parent-child relationship trees are identified by using the lazy thunk identification. Each second adjacent fragment is adjacent to the one or more fourth fragments. In the process block 396 the registry is updated with identified second adjacent fragments.
FIG. 11 illustrates a flowchart of process blocks of an example process used for generating of the one or more dedicated environments for execution of the programs using the identified cluster resources as described in the process block 110. In the process block 700 the one or more dedicated environment descriptions are phrased and validated. The execution environment description may comprise a list of all the required cluster resources, their configurations and types. The execution environment description may be in the form of an extended mark-up language (XML) file listing addresses of servers allocated within the cluster along with a list of operating system installation media, image names to be used for installing of operating systems on the servers. Phrasing the execution environment description may be creating such a description in a machine-readable format. Validating the execution environment description may be checking syntactic and semantic consistency of the execution environment description. For instance one can verify that the XML file is syntactically valid and the amount of resources requested does not exceed the acting user's quota and that operating system images are compatible with the target server's hardware. In the process block 710 the one or more virtual machines are created using the one or more identified virtual resources. In the process block 720 the one or more identified non-virtual real hardware resources are reserved. In the process block 730 the one or more identified (reserved) non-virtual real hardware resources are connected to the one or more virtual machines. This process can be readily understood on the basis of the following example. For instance the non-virtual real hardware resource is a server. Connection of this server can be performed by configuring network devices between this server and the virtual machine in a way that allows network communication between them. If the non-virtual real hardware resource is a card installed on the non-virtual real hardware server, then connection can be performed by executing the following: establishing a network connection to the non-virtual real hardware server; installing a driver that captures outgoing data and injects incoming data into this card and further into an operating system running on the non-virtual real hardware server; installing a driver that injects all the outgoing data and captures incoming data into operators of the operating system running on a virtual machine effectively simulating the presence of this card or the virtual machine; forwarding the outgoing data from the driver running on the non-virtual real hardware server to the driver running on the virtual machine and forwarding incoming data from the driver running on the virtual machine to the driver running on the non-virtual real hardware server. In the process block 740 one or more operating systems are installed on the one or more virtual machines. In the process block 750 the one or more connected non-virtual real hardware resources with the variable configurations are configured. In the process block 760 the programs and other software packages are installed on the one or more virtual machines.
FIG. 12 illustrates a modular structure of a software package operable for operating programs on a computer cluster. The software package comprises the following modules: a user module 800, an environment manager 810, a resource manager 820, a program execution manager 830, and a resource reservation database 840. The user module 800 comprises a description of dedicated execution environments 801, a list of descriptions of dedicated resources required for generation of the dedicated execution environments 802, and a list of the programs to be executed on the computer cluster 804. The user module provides the description of the dedicated execution environments to the environment manager. It further provides the description and list of the required resources to the resource manager and the list of programs to the program execution manager. The resource manager generates a registry 821 upon receiving the list and description of the dedicated resources. Further it identifies resources required for generation of the dedicated execution environments, stores them in the registry, and provides them to the environment manager for generation of the execution environments. The resource manager performs lazy thunk identification of other cluster resources and stores them in the registry. The environment manager generates the execution environments 811 upon receiving the list of identified cluster resources from the resource manager. The program execution manager generates a schedule of execution for the programs upon receiving the list of programs from the user module. The schedule is generated using a list 831 of execution conflicts of the programs in a way that the execution conflicts are avoided. Afterwards the program execution manager starts execution of the programs according to the schedule.
When execution of the programs is started the program execution manager receives requests for usage of the cluster resources and forwards them to the resource manager. The resource manager identifies the requested cluster resources, stores them in the registry, and provides them to the programs. It also performs reservations of the cluster resources, modifications in the variable configurations of the non-virtual real hardware resources with the variable configurations, rolls back the modifications of the variable configurations of the non-virtual real hardware resources with the variable configurations. The reservations and the modifications are stored in the resource reservation database 840. The resource manager reports to the program execution manager reservation and/or sharing conflicts of the cluster resources caused by the programs. As a reaction on these reports the execution manager updates the list of the execution conflicts and generates a new schedule for execution of the programs. Afterwards it starts executing programs according to the new schedule. When execution of one or more programs is finished the program execution manager reports the results of execution of the one or more programs 832 to the user module.
FIG. 13 illustrates an example software code implementation of resource handling in a “Scala” programming language. Trait Resource enables establishing of parent-child relationships between resources by providing “parent( )” and “children( )” methods. “Resource.children( )” method returns an iterable object enabling implementation of lazy thunk child resource retrieval. Classes “ServerChassis,” “Server,” “Hypervisor,” and “VirtualServer” are examples of cluster resource. Note that they override “Resource.parent( )” method and provide a specialized return type. This enables establishing of parent-child relationships between the cluster resource types. The software code illustrated in FIG. 13 may comprise deals of resource-specific operations, such as parent retrieval, children retrieval, configuration retrieval, configuration changes and rollback. Those skilled in the art will understand this software code in every detail.
FIG. 14 illustrates a resource type hierarchy or in the other words a type parent-child relationship tree. This hierarchy is used in the software code example illustrated in FIG. 13. As defined by the framework of this approach, the root cluster resource has always a type “root.” This example deals with a server chassis, which have different hardware mounted on it. The child type of the “root” type in this hierarchy is “server chassis” type. The “server chassis” type has the following types as child types: “server chassis management module,” “server management module,” “server,” “network router”, and “disk array”. In return the “server” type has the following child types: “motherboard,” “central processing unit,” “memory”, and “hypervisor”. The type “server network card” has a child type “server network card port”, the type “hypervisor” has a child type “virtual server,” the type “network router” has a child type “network router port”, and the type “disk array” has a child type “disk”.

Claims (20)

The invention claimed is:
1. A computer system for operating programs executable on a computer cluster comprising cluster resources, wherein the cluster resources comprise the following: non-virtual real hardware resources with variable configurations and virtual resources, wherein each cluster resource has a configuration description and a type, wherein each type has a unique type identification and descriptions of operations that can be performed by the cluster resource of the each type,
wherein the computer system comprises a processor and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to:
identify cluster resources for generation of one or more dedicated execution environments, wherein execution of each program requires a dedicated execution environment on the computer cluster; and
generate the one or more dedicated execution environments for execution of programs using the identified duster resources, wherein generation of each dedicated execution environment requires a plurality of virtual resources including one or more dedicated virtual resources and one or more dedicated non-virtual real hardware resources with the variable configurations, wherein each dedicated resource has an execution environment specific type and an execution environment specific configuration description, wherein each identified cluster resource matches one dedicated resource, wherein each identified cluster resource and the matching dedicated resource have the same type, and wherein the configuration description of each identified cluster resource comprises the execution environment specific configuration description of the matching dedicated resource,
wherein at least a portion of programs have execution conflicts, wherein each program has a unique identification, wherein the unique identifications of the programs having execution conflicts are stored in a list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently, wherein the instructions further cause the processor to:
split the programs in a minimum possible number of groups, wherein each group comprises no pairs of the programs having corresponding pairs of the unique identifications in the list;
generate a schedule for execution of the programs, wherein all programs of each group are scheduled for concurrent execution and the groups of the programs are scheduled for consecutive execution, wherein consecutive execution of the groups is prioritized according to a number of the programs in the groups, wherein the group comprising the highest number of programs is scheduled as the first group for execution and the group comprising the least number of programs is scheduled as the last group for execution, wherein responsive to two groups comprising the same number of programs the two groups are prioritized at random;
start execution of the programs according to the schedule in the one or mote generated dedicated execution environments;
detect an execution conflict of a pair of the programs;
abort one of the programs of the pair of the programs having the execution conflict detected;
update the list with the pair the unique identifications of the pair of the programs having the execution conflict detected;
generate a new schedule for execution of the aborted program and programs for which execution was not started yet; and
start execution of the programs according to the new schedule in the one or more generated dedicated execution environments after execution of the group comprising another program of the pair is finished.
2. The computer system of claim 1, wherein the cluster resources are hierarchically allocated within one or more resource parent-child relationship trees and linked by resource parent-child relationships with each other within the one or more resource parent-child relationship trees, wherein each resource parent-child relationship tree matches a type parent-child relationship tree comprising the hierarchically allocated types linked by type parent-child relations within the type parent-child relationship tree, wherein the resource parent-child relationships match the type parent-child relationships of their types, wherein each resource parent-child relationship tree has one top root cluster resource, wherein each type parent-child relationship tree has one top root type, wherein each top root cluster resource of each resource parent-child relationship tree has the top root type of the type parent-child relationship tree matching the each resource parent-child relationship tree, wherein the identifying of the cluster resources for the generation of the one or more dedicated execution environments comprises:
identifying first fragments of the one or more type parent-child relationship trees linking the one or more top root types of the first fragments with the environment specific types allocated at bottoms of the first fragments;
identifying second fragments of the one or more resource parent child-relationship trees matching the first fragments, wherein the identifying of the cluster resources for the generation of the one or more dedicated environments is performed using the cluster resources allocated at bottoms of the second fragments, wherein all cluster resources allocated at bottoms of the second fragments have the environment specific types;
storing the second fragments in a registry; and
identifying one or more first adjacent fragments of one or more resource parent-child relationship trees using a lazy thunk identification, wherein each first adjacent fragment is adjacent to one of the second fragments; and
updating the registry with all identified first adjacent fragments.
3. The computer system of claim 1, wherein the dedicated environment comprises a virtual machine operated by an operating system, wherein the generating of the one or more dedicated environments using the identified cluster resources comprises:
creating the virtual machine using one or more identified virtual resources;
connecting the identified non-virtual real hardware resource with the variable configuration to the virtual machine; and
installing the operating system on the virtual machine.
4. A computer program product for operating programs executable on a computer cluster comprising cluster resources, wherein the cluster resources comprise non-virtual real hardware resources with variable configurations and virtual resources, wherein each cluster resource has a configuration description and a type, wherein each type has a unique type identification and descriptions of operations that can be performed by the cluster resource of each type, wherein the computer program produce comprises a computer readable storage medium carrying computer executable code for execution by a processor, wherein execution of the computer executable code causes the processor to:
identify the cluster resources for generation of one or more dedicated execution environments, wherein execution of each program requires the dedicated execution environment on the computer cluster, and
generate the one or more dedicated execution environments for execution of programs using the identified cluster resources, wherein generation of each dedicated execution environment requires a plurality of virtual resources including one or more dedicated virtual resources and one or more dedicated non-virtual real hardware resources with the variable configurations, wherein each dedicated resource has an execution environment specific type and an execution environment specific configuration description, wherein each identified cluster resource matches one dedicated resource, wherein each identified cluster resource and the matching dedicated resource have the same type, and wherein the configuration description of each identified cluster resource comprises the execution environment specific configuration description of the matching dedicated resource,
wherein at least a portion of programs have execution conflicts, wherein each program has a unique identification, wherein the unique identifications of the programs having execution conflicts are stored in a list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently, wherein the computer executable code further causes the processor to:
split the programs in a minimum possible number of groups, wherein each group comprises no pairs of the programs having corresponding pairs of the unique identifications in the list;
generate a schedule for execution of the programs, wherein all programs of each group are scheduled for concurrent execution and the groups of the programs are scheduled for consecutive execution, wherein consecutive execution of the groups is prioritized according to a number of the programs in the groups, wherein the group comprising the highest number of programs is scheduled as the first group for execution and the group comprising the least number of programs is scheduled as the last group for execution, wherein responsive to two groups comprising the same number of programs the two groups are prioritized at random;
start execution of the programs according to the schedule in the one or more generated dedicated execution environments;
detect an execution conflict of a pair of programs;
abort one of the programs of the pair of the programs having the execution conflict detected;
update the list with the pair the unique identifications of the pair of the programs having the execution conflict detected;
generate a new schedule for execution of the aborted program and programs for which execution was not started yet; and
start execution of the programs according to the new schedule in the one or more generated dedicated execution environments after execution of the group comprising another program of the pair is finished.
5. The computer system of claim 1, wherein each program is operable for requesting usage of the cluster resource specifying the type and the configuration description, wherein the instructions further cause the processor to:
identify the cluster resource responsive to a request of the program for usage of the cluster resource, wherein the identified cluster resource has the specified type, wherein the configuration description of the identified cluster resource comprises the specified configuration description.
6. The computer system of claim 1, wherein each program is operable for requesting a modification of the variable configuration of the non-virtual real hardware resource with the variable configuration, wherein the instructions further cause the processor to:
in response to a request of a given program for a modification of the variable configuration of the non-virtual real hardware resource with the variable configuration, reserve the non-virtual real hardware resource with the variable configuration for exclusive usage by the given program and executing the requested modification of the variable configuration of the non-virtual real hardware resource with the variable configuration;
generate a record of the executed modifications of the variable configuration of the non-virtual real hardware with the variable configuration;
roll back the executed modifications of the variable configuration of said non-virtual real hardware resource with the variable configuration using the record responsive to determining execution of the given program is ended; and
responsive to rolling back the executed modifications, cancel the reserving of the non-virtual real hardware resource with the variable configuration.
7. The computer program product of claim 4, wherein each program is operable for requesting a modification of the variable configuration of the non-virtual real hardware resource with the variable configuration, wherein the computer executable code further causes the processor to:
in response to a request of a given program for a modification of the variable configuration of the non-virtual real hardware resource with the variable configuration, reserve the non-virtual real hardware resource with the variable configuration for exclusive usage by the given program and executing the requested modification of the variable configuration of the non-virtual real hardware resource with the variable configuration;
generate a record of the executed modifications of the variable configuration of the non-virtual real hardware with the variable configuration;
roll back the executed modifications of the variable configuration of said non-virtual real hardware resource with the variable configuration using the record responsive to determining execution of the given program is ended; and
responsive to rolling back the executed modifications, cancel the reserving of the non-virtual real hardware resource with the variable configuration.
8. The computer system of claim 1, wherein at least a portion of programs have execution conflicts, wherein each program has a unique identification, wherein the unique identifications of the programs having execution conflicts are stored in a list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently, wherein the instructions further cause the processor to:
a) generate an additional group;
b) assign one of the not yet assigned programs having no execution conflicts with all programs assigned to the additional group;
c) repeat step b) until there are no programs left that have no execution conflicts with any of the programs of the additional group;
d) iteratively repeat the steps a)-c), wherein the repeating is continued until all programs are assigned to one or more groups, wherein exactly one additional group is generated during each repeating of the steps a)-c), wherein all pairs comprising at least one unique identification of any of the programs assigned to any previously generated additional group are considered as being deleted from the list during the subsequent repeating of the steps a)-c);
generate a schedule for execution of the programs, wherein all programs of each group are scheduled for concurrent execution and the groups of the programs are scheduled for consecutive execution, wherein consecutive execution of the groups is prioritized according to a number of the programs in the groups, wherein the group comprising the highest number of programs is scheduled as the first group for execution and the group comprising the least number of programs is scheduled as the last group for execution, wherein responsive to determining two groups comprise the same number of programs, the two groups are prioritized at random;
start of execution of the programs according to the schedule in the one or more generated dedicated execution environments;
detect an execution conflict of a pair of the programs;
abort one of the programs of the pair of the programs having the execution conflict detected;
update the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected; and
responsive to updating the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected, identify all programs within the pairs in the list that comprise the unique identification of the aborted program;
responsive to identifying that one or more not yet executed groups do not comprise any identified program, assign the aborted program to the not yet executed group not comprising any identified programs and having the highest priority for execution among the not yet executed groups; and
responsive to identifying that one or more not yet executed groups do comprise any identified program, schedule execution of the aborted program after execution of the last group.
9. The computer system of claim 1, wherein the aborted program of the pair of the programs is the program having a larger number of the cluster resources requested for usage in comparison with another program of the pair.
10. The computer system of claim 1, wherein each program has a workload to be processed during execution, wherein the aborted program of the pair of the programs is the program having a lower percentage of the executed workload in comparison with another program of the pair.
11. The computer system of claim 1, wherein the aborted program of the pair of the programs is the program having a shorter duration of execution in comparison with another program of the pair.
12. The computer system of claim 2, wherein identifying the cluster resource upon the request of the program for usage of the cluster resource comprises:
checking whether at least one of the cluster resources allocated in the fragments of the one or more resource parent-child relationship trees stored in the registry has the specified type and has the configuration description comprising the specified configuration description;
responsive to determining that at least one of the luster resources allocated in the fragments of the one or more resource parent-child relationship trees stored in the registry has the specified type and has the configuration description comprising the specified configuration description, the identifying of the cluster resource upon the request of the program for usage of the cluster resource is performed using the fragments of one or more resource parent-child relationship trees stored in the registry; and
responsive to determining that at least one of the luster resources allocated in the fragments of the one or more resource parent-child relationship trees stored in the registry does not have the specified type or does not have the configuration description comprising the specified configuration description:
identifying one or more third fragments of the one or more type parent-child relationship trees linking the one or more top root types of the one or more type parent-child relationship trees with the specified type allocated at one or more bottoms of the one or more third fragments;
identifying one or more fourth fragments of the one or more resource parent child-relationship trees matching the one or more third fragments, wherein the identifying of the cluster resource responsive to the request of the given program for usage of the cluster resource is performed using the cluster resources allocated at one or more bottoms of the one or more fourth fragments, wherein all cluster resources allocated at the one or more bottoms of the one or more fourth fragments have the specified types;
updating the registry with all fourth fragments;
identifying one or more second adjacent fragments of the one or more resource parent-child relationship trees using the lazy thunk identification, wherein each second adjacent fragment is adjacent to one of the one or more fourth fragments; and
updating the registry with the one or more second adjacent fragments.
13. The computer system of claim 2, wherein the identifying of the one or more fragments of the one or more resource parent child-relationship trees is performed applying one or more predefined identification constraints restricting the identifying of the fragments of the one or more resource parent-child relationship trees.
14. The computer program product of claim 4, wherein at least a portion of programs have execution conflicts, wherein each program has a unique identification, wherein the unique identifications of the programs having execution conflicts are stored in a list comprising one or more pairs of the unique identifications of the programs having execution conflicts when both programs of any pair are executed concurrently, wherein the computer executable code further causes the processor to:
a) generate an additional group;
b) assign one of the not yet assigned programs having no execution conflicts with all programs assigned to the additional group;
c) repeat step b) until there are no programs left that have no execution conflicts with any of the programs of the additional group;
d) iteratively repeat the steps a)-c), wherein the repeating is continued until all programs are assigned to one or more groups, wherein exactly one additional group is generated during each repeating of the steps a)-c), wherein all pairs comprising at least one unique identification of any of the programs assigned to any previously generated additional group are considered as being deleted from the list during the subsequent repeating of the steps a)-c);
generate a schedule for execution of the programs, wherein all programs of each group are scheduled for concurrent execution and the groups of the programs re scheduled for consecutive execution, wherein consecutive execution of the groups is prioritized according to a number of the programs in the groups, wherein the group comprising the highest number of programs is scheduled as the first group for execution and the group comprising the least number of programs is scheduled as the last group for execution, wherein responsive to determining two groups comprise the same number of programs, the two groups are prioritized at random;
start of execution of the programs according to the schedule in the one or more generated dedicated execution environments;
detect an execution conflict of a pair of the programs;
abort one of the programs of the pair of the programs having the execution conflict detected;
update the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected; and
responsive to updating the list with the pair of the unique identifications of the pair of the programs having the execution conflict detected, identify all programs within the pairs in the list that comprise the unique identification of the aborted program;
responsive to identifying that one or more not yet executed groups do not comprise any identified program, assign the aborted program to the not yet executed group not comprising any identified programs and having the highest priority for execution among the not yet executed groups; and
responsive to identifying that one or more not yet executed groups do comprise any identified program, schedule execution of the aborted program after execution of the last group.
15. The computer program product of claim 4, wherein the cluster resources are hierarchically allocated within one or more resource parent-child relationship trees and linked by resource parent-child relationships with each other within the one or more resource parent-child relationship trees, wherein each resource parent-child relationship tree matches a type parent-child relationship tree comprising the hierarchically allocated types linked by type parent-child relations within the type parent-child relationship tree, wherein the resource parent-child relationships match the type parent-child relationships of their types, wherein each resource parent-child relationship tree has one top root cluster resource, wherein each type parent-child relationship tree has one top root type, wherein each top root cluster resource of each resource parent-child relationship tree has the top root type of the type parent-child relationship tree matching the each resource parent-child relationship tree, wherein the identifying of the cluster resources for the generation of the one or more dedicated execution environments comprises:
identifying first fragments of the one or more type parent-child relationship trees linking the one or more top root types of the first fragments with the environment specific types allocated at bottoms of the first fragments;
identifying second fragments of the one or more resource parent child-relationship trees matching the first fragments, wherein the identifying of the cluster resources for the generation of the one or more dedicated environments is performed using the cluster resources allocated at bottoms of the second fragments, wherein all cluster resources allocated at bottoms of the second fragments have the environment specific types;
storing the second fragments in a registry; and
identifying one or more first adjacent fragments of one or more resource parent-child relationship trees using a lazy thunk identification, wherein each first adjacent fragment is adjacent to one of the second fragments; and
updating the registry with all identified first adjacent fragments.
16. The computer program product of claim 4, wherein the dedicated environment comprises a virtual machine operated by an operating system, wherein the generating of the one or more dedicated environments using the identified cluster resources comprises:
creating the virtual machine using one or more identified virtual resources;
connecting the identified non-virtual real hardware resource with the variable configuration to the virtual machine; and
installing the operating system on the virtual machine.
17. The computer program product of claim 4, wherein each program is operable for requesting usage of the cluster resource specifying the type and the configuration description, wherein the computer executable code further causes the processor to:
identify the cluster resource responsive to a request of the program for usage of the cluster resource, wherein the identified cluster resource has the specified type, wherein the configuration description of the identified cluster resource comprises the specified configuration description.
18. The computer program product of claim 4, wherein the aborted program of the pair of the programs is the program having a larger number of the cluster resources requested for usage in comparison with another program of the pair.
19. The computer program product of claim 4, wherein each program has a workload to be processed during execution, wherein the aborted program of the pair of the programs is the program having a lower percentage of the executed workload in comparison with another program of the pair.
20. The computer program product of claim 4, wherein the aborted program of the pair of the programs is the program having a shorter duration of execution in comparison with another program of the pair.
US14/315,518 2013-10-07 2014-06-26 Operating programs on a computer cluster Expired - Fee Related US9542226B2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US14/482,069 US10025630B2 (en) 2013-10-07 2014-09-10 Operating programs on a computer cluster
US15/398,867 US10310900B2 (en) 2013-10-07 2017-01-05 Operating programs on a computer cluster

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB1317670.6A GB2518894A (en) 2013-10-07 2013-10-07 A method and a system for operating programs on a computer cluster
GB1317670.6 2013-10-07

Related Child Applications (2)

Application Number Title Priority Date Filing Date
US14/482,069 Continuation US10025630B2 (en) 2013-10-07 2014-09-10 Operating programs on a computer cluster
US15/398,867 Continuation US10310900B2 (en) 2013-10-07 2017-01-05 Operating programs on a computer cluster

Publications (2)

Publication Number Publication Date
US20150100968A1 US20150100968A1 (en) 2015-04-09
US9542226B2 true US9542226B2 (en) 2017-01-10

Family

ID=49630265

Family Applications (3)

Application Number Title Priority Date Filing Date
US14/315,518 Expired - Fee Related US9542226B2 (en) 2013-10-07 2014-06-26 Operating programs on a computer cluster
US14/482,069 Expired - Fee Related US10025630B2 (en) 2013-10-07 2014-09-10 Operating programs on a computer cluster
US15/398,867 Expired - Fee Related US10310900B2 (en) 2013-10-07 2017-01-05 Operating programs on a computer cluster

Family Applications After (2)

Application Number Title Priority Date Filing Date
US14/482,069 Expired - Fee Related US10025630B2 (en) 2013-10-07 2014-09-10 Operating programs on a computer cluster
US15/398,867 Expired - Fee Related US10310900B2 (en) 2013-10-07 2017-01-05 Operating programs on a computer cluster

Country Status (2)

Country Link
US (3) US9542226B2 (en)
GB (1) GB2518894A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150100961A1 (en) * 2013-10-07 2015-04-09 International Business Machines Corporation Operating Programs on a Computer Cluster
US10162663B2 (en) * 2014-02-17 2018-12-25 Hitachi, Ltd. Computer and hypervisor-based resource scheduling method

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160285957A1 (en) * 2015-03-26 2016-09-29 Avaya Inc. Server cluster profile definition in a distributed processing network
US10452442B2 (en) * 2015-11-27 2019-10-22 Huawei Technologies Co., Ltd. System and method for resource management
JP6588106B2 (en) * 2016-01-07 2019-10-09 株式会社日立製作所 Computer system and computer control method
US10496331B2 (en) * 2017-12-04 2019-12-03 Vmware, Inc. Hierarchical resource tree memory operations
CN110008073B (en) * 2019-04-11 2023-01-10 苏州浪潮智能科技有限公司 Hardware platform differential shielding method, device, equipment and readable storage medium
US10977072B2 (en) 2019-04-25 2021-04-13 At&T Intellectual Property I, L.P. Dedicated distribution of computing resources in virtualized environments
US20230106414A1 (en) * 2021-10-06 2023-04-06 Vmware, Inc. Managing updates to hosts in a computing environment based on fault domain host groups

Citations (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6003075A (en) 1997-07-07 1999-12-14 International Business Machines Corporation Enqueuing a configuration change in a network cluster and restore a prior configuration in a back up storage in reverse sequence ordered
US6247109B1 (en) 1998-06-10 2001-06-12 Compaq Computer Corp. Dynamically assigning CPUs to different partitions each having an operation system instance in a shared memory space
US20040249947A1 (en) * 2003-05-22 2004-12-09 Hewlett-Packard Development Company, L.P. Concurrent cluster environment
US20050223362A1 (en) 2004-04-02 2005-10-06 Gemstone Systems, Inc. Methods and systems for performing unit testing across multiple virtual machines
US20080189468A1 (en) * 2007-02-02 2008-08-07 Vmware, Inc. High Availability Virtual Machine Cluster
US20090204964A1 (en) * 2007-10-12 2009-08-13 Foley Peter F Distributed trusted virtualization platform
US20100017517A1 (en) 2008-07-17 2010-01-21 Daisuke Arai Network operations management method and apparatus
US20100031325A1 (en) * 2006-12-22 2010-02-04 Virtuallogix Sa System for enabling multiple execution environments to share a device
US20100070725A1 (en) * 2008-09-05 2010-03-18 Anand Prahlad Systems and methods for management of virtualization data
US7774191B2 (en) * 2003-04-09 2010-08-10 Gary Charles Berkowitz Virtual supercomputer
JP2011050514A (en) 2009-08-31 2011-03-17 Yukio Konishi Measuring device for artificial leg assembly
US20110176441A1 (en) 2010-01-21 2011-07-21 Fujitsu Limited Computer-readable medium storing test environment creation program, test environment creation method, and test device
US20110244440A1 (en) 2010-03-14 2011-10-06 Steve Saxon Cloud Based Test Environment
US8078728B1 (en) 2006-03-31 2011-12-13 Quest Software, Inc. Capacity pooling for application reservation and delivery
US8166458B2 (en) 2005-11-07 2012-04-24 Red Hat, Inc. Method and system for automated distributed software testing
US8171473B2 (en) * 2007-08-31 2012-05-01 International Business Machines Corporation Method and apparatus for determining a service cluster topology based on static analysis
US20120110086A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Ensemble having one or more computing systems and a controller thereof
US20120110164A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Managing a workload of a plurality of virtual servers of a computing environment
US20120110588A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Unified resource manager providing a single point of control
US20120110155A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Management of a data network of a computing environment
US20120110154A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Integration of heterogeneous computing systems into a hybrid computing system
US8181174B2 (en) 2007-12-28 2012-05-15 Accenture Global Services Limited Virtual machine configuration system
US8219987B1 (en) 2007-08-24 2012-07-10 Vmware, Inc. Optimized virtual machine specification for provisioning application specific runtime environment
DE102012203534A1 (en) 2011-03-14 2012-09-20 International Business Machines Corp. Hardware characterization for the application in relation to virtual environments
EP2503449A2 (en) 2011-03-25 2012-09-26 Unisys Corporation Single development test environment
US20120266135A1 (en) 2011-01-03 2012-10-18 Ebay Inc. On-demand software test environment generation
US20120317567A1 (en) * 2011-06-07 2012-12-13 International Business Machines Corporation Virtual network configuration and management
US20120324281A1 (en) 2011-06-20 2012-12-20 QuorumLabs Recovery Node Testing
US20130297964A1 (en) * 2012-05-03 2013-11-07 Vmware, Inc. Virtual Machine Placement With Automatic Deployment Error Recovery
US20130346987A1 (en) * 2012-06-21 2013-12-26 Kristopher Len Raney Systems and methods for distributing tasks and/or processing recources in a system
US20140019964A1 (en) * 2012-07-13 2014-01-16 Douglas M. Neuse System and method for automated assignment of virtual machines and physical machines to hosts using interval analysis
US20140019965A1 (en) * 2012-07-13 2014-01-16 Douglas M. Neuse System and method for automated assignment of virtual machines and physical machines to hosts with right-sizing
US20140019966A1 (en) * 2012-07-13 2014-01-16 Douglas M. Neuse System and method for continuous optimization of computing systems with automated assignment of virtual machines and physical machines to hosts
US20140101657A1 (en) * 2012-10-08 2014-04-10 International Business Machines Corporation Concurrent hypervisor replacement
US8904008B2 (en) * 2012-01-09 2014-12-02 Microsoft Corporation Assignment of resources in virtual machine pools
US20140380307A1 (en) * 2013-06-25 2014-12-25 Vmware, Inc. Performance-driven resource management in a distributed computer system
US20140380308A1 (en) * 2013-06-25 2014-12-25 Vmware, Inc. Methods and apparatus to generate a customized application blueprint

Family Cites Families (29)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6442585B1 (en) * 1997-11-26 2002-08-27 Compaq Computer Corporation Method for scheduling contexts based on statistics of memory system interactions in a computer system
US7398525B2 (en) * 2002-10-21 2008-07-08 International Business Machines Corporation Resource scheduling in workflow management systems
US8209680B1 (en) * 2003-04-11 2012-06-26 Vmware, Inc. System and method for disk imaging on diverse computers
CA2559584A1 (en) * 2004-03-13 2005-09-29 Cluster Resources, Inc. System and method of providing a self-optimizing reservation in space of compute resources
US8850060B1 (en) * 2004-04-19 2014-09-30 Acronis International Gmbh Network interface within a designated virtual execution environment (VEE)
US7934215B2 (en) * 2005-01-12 2011-04-26 Microsoft Corporation Smart scheduler
US8429630B2 (en) * 2005-09-15 2013-04-23 Ca, Inc. Globally distributed utility computing cloud
US7987004B2 (en) * 2007-02-27 2011-07-26 Rockwell Automation Technologies, Inc. Scalability related to controller engine instances
JP4874140B2 (en) * 2007-03-20 2012-02-15 京セラミタ株式会社 Job scheduler, job scheduling method, and job control program
US20090077550A1 (en) * 2007-09-13 2009-03-19 Scott Rhine Virtual machine schedular with memory access control
US8635380B2 (en) * 2007-12-20 2014-01-21 Intel Corporation Method, system and apparatus for handling events for partitions in a socket with sub-socket partitioning
US8443363B1 (en) * 2008-05-30 2013-05-14 Symantec Corporation Coordinated virtualization activities
US8291414B2 (en) * 2008-12-11 2012-10-16 International Business Machines Corporation Shared resource service provisioning using a virtual machine manager
US8392926B2 (en) * 2010-04-06 2013-03-05 International Business Machines Corporation Scheduling heterogeneous partitioned resources with sharing constraints
US8510749B2 (en) * 2010-05-27 2013-08-13 International Business Machines Corporation Framework for scheduling multicore processors
US8407689B2 (en) * 2010-06-25 2013-03-26 Microsoft Corporation Updating nodes considering service model constraints
US8635624B2 (en) * 2010-10-21 2014-01-21 HCL America, Inc. Resource management using environments
US8954967B2 (en) * 2011-05-31 2015-02-10 International Business Machines Corporation Adaptive parallel data processing
US9098608B2 (en) * 2011-10-28 2015-08-04 Elwha Llc Processor configured to allocate resources using an entitlement vector
US9354934B2 (en) * 2012-01-05 2016-05-31 International Business Machines Corporation Partitioned shared processor interrupt-intensive task segregator
US20130332778A1 (en) * 2012-06-07 2013-12-12 Vmware, Inc. Performance-imbalance-monitoring processor features
US9104449B2 (en) * 2012-06-18 2015-08-11 Google Inc. Optimized execution of dynamic languages
AT513314A1 (en) * 2012-06-25 2014-03-15 Fts Computertechnik Gmbh Method for building optimal timed paths in a large computer network
CN103870317B (en) * 2012-12-10 2017-07-21 中兴通讯股份有限公司 Method for scheduling task and system in cloud computing
US9298511B2 (en) * 2013-03-15 2016-03-29 International Business Machines Corporation Resolving deployment conflicts in heterogeneous environments
US9292349B2 (en) * 2013-03-15 2016-03-22 International Business Machines Corporation Detecting deployment conflicts in heterogenous environments
GB2518894A (en) * 2013-10-07 2015-04-08 Ibm A method and a system for operating programs on a computer cluster
US20150143375A1 (en) * 2013-11-18 2015-05-21 Unisys Corporation Transaction execution in systems without transaction support
US9703951B2 (en) * 2014-09-30 2017-07-11 Amazon Technologies, Inc. Allocation of shared system resources

Patent Citations (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6003075A (en) 1997-07-07 1999-12-14 International Business Machines Corporation Enqueuing a configuration change in a network cluster and restore a prior configuration in a back up storage in reverse sequence ordered
US6247109B1 (en) 1998-06-10 2001-06-12 Compaq Computer Corp. Dynamically assigning CPUs to different partitions each having an operation system instance in a shared memory space
US7774191B2 (en) * 2003-04-09 2010-08-10 Gary Charles Berkowitz Virtual supercomputer
US20040249947A1 (en) * 2003-05-22 2004-12-09 Hewlett-Packard Development Company, L.P. Concurrent cluster environment
US20050223362A1 (en) 2004-04-02 2005-10-06 Gemstone Systems, Inc. Methods and systems for performing unit testing across multiple virtual machines
US8166458B2 (en) 2005-11-07 2012-04-24 Red Hat, Inc. Method and system for automated distributed software testing
US8078728B1 (en) 2006-03-31 2011-12-13 Quest Software, Inc. Capacity pooling for application reservation and delivery
US20100031325A1 (en) * 2006-12-22 2010-02-04 Virtuallogix Sa System for enabling multiple execution environments to share a device
US20080189468A1 (en) * 2007-02-02 2008-08-07 Vmware, Inc. High Availability Virtual Machine Cluster
US8219987B1 (en) 2007-08-24 2012-07-10 Vmware, Inc. Optimized virtual machine specification for provisioning application specific runtime environment
US8171473B2 (en) * 2007-08-31 2012-05-01 International Business Machines Corporation Method and apparatus for determining a service cluster topology based on static analysis
US20090204964A1 (en) * 2007-10-12 2009-08-13 Foley Peter F Distributed trusted virtualization platform
US8181174B2 (en) 2007-12-28 2012-05-15 Accenture Global Services Limited Virtual machine configuration system
US20100017517A1 (en) 2008-07-17 2010-01-21 Daisuke Arai Network operations management method and apparatus
US20100070725A1 (en) * 2008-09-05 2010-03-18 Anand Prahlad Systems and methods for management of virtualization data
JP2011050514A (en) 2009-08-31 2011-03-17 Yukio Konishi Measuring device for artificial leg assembly
US20110176441A1 (en) 2010-01-21 2011-07-21 Fujitsu Limited Computer-readable medium storing test environment creation program, test environment creation method, and test device
US20110244440A1 (en) 2010-03-14 2011-10-06 Steve Saxon Cloud Based Test Environment
US20120110588A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Unified resource manager providing a single point of control
US20120110155A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Management of a data network of a computing environment
US20120110154A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Integration of heterogeneous computing systems into a hybrid computing system
US20120110164A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Managing a workload of a plurality of virtual servers of a computing environment
US20120110086A1 (en) * 2010-11-02 2012-05-03 International Business Machines Corporation Ensemble having one or more computing systems and a controller thereof
US20120266135A1 (en) 2011-01-03 2012-10-18 Ebay Inc. On-demand software test environment generation
DE102012203534A1 (en) 2011-03-14 2012-09-20 International Business Machines Corp. Hardware characterization for the application in relation to virtual environments
EP2503449A2 (en) 2011-03-25 2012-09-26 Unisys Corporation Single development test environment
US20120317567A1 (en) * 2011-06-07 2012-12-13 International Business Machines Corporation Virtual network configuration and management
US20120324281A1 (en) 2011-06-20 2012-12-20 QuorumLabs Recovery Node Testing
US8904008B2 (en) * 2012-01-09 2014-12-02 Microsoft Corporation Assignment of resources in virtual machine pools
US20130297964A1 (en) * 2012-05-03 2013-11-07 Vmware, Inc. Virtual Machine Placement With Automatic Deployment Error Recovery
US20130346987A1 (en) * 2012-06-21 2013-12-26 Kristopher Len Raney Systems and methods for distributing tasks and/or processing recources in a system
US20140019964A1 (en) * 2012-07-13 2014-01-16 Douglas M. Neuse System and method for automated assignment of virtual machines and physical machines to hosts using interval analysis
US20140019965A1 (en) * 2012-07-13 2014-01-16 Douglas M. Neuse System and method for automated assignment of virtual machines and physical machines to hosts with right-sizing
US20140019966A1 (en) * 2012-07-13 2014-01-16 Douglas M. Neuse System and method for continuous optimization of computing systems with automated assignment of virtual machines and physical machines to hosts
US20140101657A1 (en) * 2012-10-08 2014-04-10 International Business Machines Corporation Concurrent hypervisor replacement
US20140380307A1 (en) * 2013-06-25 2014-12-25 Vmware, Inc. Performance-driven resource management in a distributed computer system
US20140380308A1 (en) * 2013-06-25 2014-12-25 Vmware, Inc. Methods and apparatus to generate a customized application blueprint

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
Foster, Ian, et al. "Virtual clusters for grid communities." Cluster Computing and the Grid, 2006. CCGRID 06. Sixth IEEE International Symposium on. vol. 1. IEEE, 2006. *
Gao, Jerry et al., "Cloud Testing-Issues, Challenges, Needs and Practice", Software Engineering: An International Journal (SEIJ), vol. 1, No. 1, Sep. 2011, 15 pages.
Krsul, Ivan, et al. "Vmplants: Providing and managing virtual machine execution environments for grid computing." Supercomputing, 2004. Proceedings of the ACM/IEEE SC2004 Conference. IEEE, 2004. *
List of IBM Patents or Patent Applications Treated as Related (Appendix P), 2 pages.
Search Report under Section 17(5) dated Feb. 26, 2014, International Application No. GB1317670.6, 3 pages.
Tang, Hong, Kai Shen, and Tao Yang. "Program transformation and runtime support for threaded MPI execution on shared-memory machines." ACM Transactions on Programming Languages and Systems (TOPLAS) 22.4 (2000): 673-700. *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150100961A1 (en) * 2013-10-07 2015-04-09 International Business Machines Corporation Operating Programs on a Computer Cluster
US10025630B2 (en) * 2013-10-07 2018-07-17 International Business Machines Corporation Operating programs on a computer cluster
US10310900B2 (en) * 2013-10-07 2019-06-04 International Business Machines Corporation Operating programs on a computer cluster
US10162663B2 (en) * 2014-02-17 2018-12-25 Hitachi, Ltd. Computer and hypervisor-based resource scheduling method

Also Published As

Publication number Publication date
GB2518894A (en) 2015-04-08
US10310900B2 (en) 2019-06-04
US20170116036A1 (en) 2017-04-27
US20150100968A1 (en) 2015-04-09
US20150100961A1 (en) 2015-04-09
GB201317670D0 (en) 2013-11-20
US10025630B2 (en) 2018-07-17

Similar Documents

Publication Publication Date Title
US10310900B2 (en) Operating programs on a computer cluster
US10735345B2 (en) Orchestrating computing resources between different computing environments
US9684502B2 (en) Apparatus, systems, and methods for distributed application orchestration and deployment
US9413604B2 (en) Instance host configuration
US8584121B2 (en) Using a score-based template to provide a virtual machine
US9201557B2 (en) Extensible framework to support different deployment architectures
JP6658882B2 (en) Control device, VNF placement destination selection method and program
US20150186129A1 (en) Method and system for deploying a program module
WO2019060228A1 (en) Systems and methods for instantiating services on top of services
TW201229795A (en) Web service patterns for globally distributed service fabric
US8966025B2 (en) Instance configuration on remote platforms
EP4053699A1 (en) Instance host configuration
CN101159596A (en) Method and apparatus for deploying servers
CN113645262A (en) Cloud computing service system and method
US20220179711A1 (en) Method For Platform-Based Scheduling Of Job Flow
CN117076096A (en) Task flow execution method and device, computer readable medium and electronic equipment
US8850440B2 (en) Managing the processing of processing requests in a data processing system comprising a plurality of processing environments
KR102156656B1 (en) System and method for creating stack of virtual machine
US11953972B2 (en) Selective privileged container augmentation
US20230325267A1 (en) Selective privileged container augmentation
US11803448B1 (en) Faster restart of task nodes using periodic checkpointing of data sources
CN111741097B (en) Method for tenant to monopolize node, computer equipment and storage medium
CN114327752A (en) Micro-service configuration method, device and equipment
CN117112181A (en) Data synchronization method and device, computer readable storage medium and electronic equipment
CN116860279A (en) Workload execution on backend systems

Legal Events

Date Code Title Description
AS Assignment

Owner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW Y

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:BIESWANGER, ANDREAS;LEOSHKEVICH, ILIJA;SIGNING DATES FROM 20140619 TO 20140623;REEL/FRAME:033184/0698

STCF Information on status: patent grant

Free format text: PATENTED CASE

FEPP Fee payment procedure

Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

LAPS Lapse for failure to pay maintenance fees

Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

STCH Information on status: patent discontinuation

Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362

FP Lapsed due to failure to pay maintenance fee

Effective date: 20210110